World Map with Confirmed and Death Cases
Bar Charts with descending order
Cumulated and Daily Cases over Time
World
Selected Countries
The plot shows the extreme forecast increase in case of unchecked exponentiell growth. The dark shaded regions show 80% rsp. 95% prediction intervals. These prediction intervals are displaying the uncertainty in forecasts based on the linear regression over the past 9 days.
China and South Korea significantly slowed down exponential growth. Therefore, their lines in the chart with the log10 scale no longer have a significant.
Most other countries are still in a phase of more or less unchecked exponentiell growth. For Italy, the reduced exponential growth is reflected in a reduced slope of the cumulated cases.
Doubling Time and Forecast
The forecasted cases for the next 14 days are calculated ‘only’ from the linear regression of the logarithmic data and are not considering any effects of measures in place. In addition data inaccuracies are not taken into account, especially relevant for the confirmed cases.
Therefore the 14 days forecast is only an indication for the direction of an unchecked exponentiell growth.
| Country | Case_Type | T_doubling | last_day | FC_next_day | FC_14days |
|---|---|---|---|---|---|
| Austria | Confirmed | 5.8 | 9’618 | 11’612 | 55’112 |
| France | Confirmed | 5.5 | 45’170 | 53’625 | 273’138 |
| Germany | Confirmed | 5.4 | 66’885 | 80’953 | 425’886 |
| India | Confirmed | 5.0 | 1’251 | 1’449 | 8’714 |
| Italy | Confirmed | 10.0 | 101’739 | 112’347 | 277’518 |
| South Korea | Confirmed | 67.2 | 9’661 | 9’752 | 11’151 |
| Spain | Confirmed | 4.9 | 87’956 | 109’141 | 679’654 |
| United States of America | Confirmed | 3.5 | 161’807 | 213’231 | 2’805’996 |
| World | Confirmed | 6.4 | 782’365 | 895’114 | 3’624’417 |
| Austria | Deaths | 2.9 | 108 | 142 | 3’142 |
| France | Deaths | 3.7 | 3’030 | 3’960 | 44’983 |
| Germany | Deaths | 2.8 | 645 | 874 | 20’847 |
| India | Deaths | 3.7 | 32 | 41 | 478 |
| Italy | Deaths | 7.3 | 11’591 | 13’102 | 44’907 |
| South Korea | Deaths | 14.8 | 158 | 166 | 306 |
| Spain | Deaths | 3.8 | 7’716 | 10’120 | 109’211 |
| United States of America | Deaths | 2.8 | 2’978 | 4’099 | 104’672 |
| World | Deaths | 5.8 | 37’582 | 43’241 | 204’706 |
The forecast accuracy is checked by using the forecast method for the nine days before the past three days (training data). Subsequent forecasting of the past three days enables comparison with the real data of these days (test data).
The comparison is also an early indicator if the exponential growth is declining. However, possible changes in underreporting (in particular the proportion confirmed / actually infected) requires careful interpretation.
The number of confirmed cases can be used as a time delayed predictor of the number of deaths. This will allow comclusions on the time period confirmed to death. More inportant the country specific case fatality rate (CFR, proportion of deaths from confirmed cases) indicates the country specific testing.
Overall a rough conclusion on the country specific proportion of infected to confirmed cases is feasible if the infection fatality rate (IFR, confiremd cases plus all asymptomatic and undiagnosed infections) is assumed to be country independent and the IFR is known (assumption by RKI ~ 0.56%, bottom of existing estimates, see https://www.rki.de/DE/Content/InfAZ/N/Neuartiges_Coronavirus/Modellierung_Deutschland.pdf?__blob=publicationFile ).
In the model paper RKI assumes for the
Depending on the country-specific test frequency (late or early tests), the
*lag_days - time from receipt of the confirmed test result to death, Confirmed to Death, is about 11-13 days.
Note: these methods are also used for example for advertising campaigns. The campaign impact on sales will be some time beyond the end of the campaign, and sales in one month will depend on the advertising expenditure in each of the past few months (see https://otexts.com/fpp3/lagged-predictors.html).
Data Source
Data files are provided by Johns Hopkins University on GitHub
https://github.com/CSSEGISandData/COVID-19/tree/master/csse_covid_19_data/csse_covid_19_time_series
Note: as of 2020-03-27 recovered cases are provided again
The data are visualized on their excellent Dashboard
Johns Hopkins University Dashboard
https://coronavirus.jhu.edu/map.html
Further links
WHO Dashboard
https://experience.arcgis.com/experience/685d0ace521648f8a5beeeee1b9125cd
Robert Koch Institut, Germany
https://www.rki.de/DE/Content/InfAZ/N/Neuartiges_Coronavirus/Fallzahlen.html?nn=13490888
Wikipedia - Exponential Growth
https://en.wikipedia.org/wiki/Exponential_growth
Code Source
Code is based on ideas from https://rpubs.com/TimoBoll/583802